Tuesday, June 29, 2010

(empo-tymshft) The importance of a timeframe

Who is the best NBA basketball team?

Seems like a simple question, right?

Inasmuch as I live in the Los Angeles area, you can guess what the answer to that question is around here. Since the Lakers won the championship for the 2009-2010 season, they are clearly the best team in basketball.

However, the results in any one year are partially attributable to luck. What if Player X had never been injured? What if Player Y didn't happen to make that critical shot in a critical game?

OK, the Lakers fans will respond, let's look at the last three years. During that period, the Lakers were clearly the dominant team.

Excuse me for a moment, but I think I hear a dissenting view from the woman in the green shirt.

"Has there been any team who has won 17 championships? Yes, one - the Boston Celtics. And we won all 17 of our championships in the same city, in the same league. We don't have to count Minneapolis wins or BAA championships in our total."

Of course, the Boston Celtics of 1957 differed tremendously from the Boston Celtics of 2008. The arena was different, the players were different, the game was different. Is it reasonable to look at a period spanning a half-century or more?

What about the last twenty years, Chicago Bulls fans will argue? (6 Bulls championships, 5 Lakers championships, 4 San Antonio Spurs championships.)

Until the Lakers' recent resurgence, the Spurs could lay claim to being the dominant team of the decade.

And until the Lakers' recent resurgence, there was another claimant to the throne - "whatever team Shaquille O'Neal is on." (3 championships with the Lakers, one with the Miami Heat.)

So you can see that definitions of a problem can be significantly impacted by the time scale that is used to analyze the problem. I can guarantee that the results of a three coin toss test will be dramatically different than the results of a 1,000 coin toss test.

Now one can argue that you should use a time scale that is most relevant to the problem that you wish to solve, but as we have seen, relevance is open to interpretation.

Now if you will excuse me, I need to finish writing this Best Blog Post Ever.
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